You're in charge of Britain's artificial intelligence strategy. You just announced £500 million in taxpayer money to supercharge the country's AI sector. Naturally, reporters want to know: what AI tools do you use?

"I don't use AI," Science, Innovation and Technology Secretary Liz Kendall told the BBC this week.

The admission came just days after Kendall unveiled the government's latest push to position Britain as an AI powerhouse. The fund aims to accelerate British AI companies and keep the UK competitive with the United States and China in the global race for artificial intelligence dominance.

But Kendall's personal abstention from the technology she's tasked with promoting raises an uncomfortable question: How can you effectively regulate and champion something you don't actually use?

The Credibility Problem

To be fair, Kendall isn't alone among policymakers who talk AI without walking AI. Many legislators worldwide craft tech policy based on briefings and expert testimony rather than hands-on experience. That's normal — you don't need to be a pilot to regulate aviation.

But AI is different. It's not infrastructure you occasionally interact with. It's productivity software that's rapidly embedding itself into everyday work. Tools like ChatGPT, Claude, and Copilot are already reshaping how millions of people write emails, analyze data, and research topics.

When a cabinet minister responsible for technology policy says she doesn't use these tools, it suggests a troubling distance between the government's AI ambitions and the lived reality of the technology. How do you assess AI's workplace impact if you're not experiencing it yourself? How do you understand its limitations — the hallucinations, the biases, the subtle ways it can mislead — without seeing them firsthand?

Following the Money

The £500 million fund Kendall announced represents a significant bet on Britain's AI future. The government is positioning this investment as essential to keeping pace with massive AI spending in the US and China, where tech giants and state-backed initiatives are pouring tens of billions into development.

But here's what the announcement doesn't address: who actually benefits from this spending? The money flows to AI companies and research institutions, not to workers whose jobs these systems might disrupt or transform. There's no comparable fund for retraining programs or social safety nets for displaced workers.

According to reporting by the BBC, the fund will focus on "boosting British AI firms" — a phrase that typically means supporting startups and established tech companies seeking to scale up. It's the familiar playbook: subsidize innovation, hope the benefits trickle down.

The Adoption Gap

Kendall's non-use of AI actually puts her in the majority. Despite breathless media coverage, most professionals still don't regularly use AI tools in their work. Recent surveys suggest adoption rates hover around 20-30% in white-collar jobs, concentrated heavily among tech workers and early adopters.

This gap between AI hype and AI reality matters for policy. If the minister doesn't use AI, perhaps it's because — like most people — she hasn't found a compelling use case in her daily work. That's useful information. It suggests the technology may not be as immediately transformative as vendors claim.

But it also means Britain's AI strategy is being shaped by someone experiencing the technology primarily through corporate pitches and optimistic forecasts rather than practical limitations. You learn different lessons from a demo than from actually trying to use AI for real work.

What She Could Learn

If Kendall did experiment with AI tools, she might discover insights that would improve her policymaking. She'd encounter the systems' tendency to confidently state falsehoods. She'd see how they struggle with nuance and context. She'd notice how they can accelerate certain tasks while introducing new types of errors that require careful human review.

She might also find genuinely useful applications — and that hands-on knowledge would help her distinguish between AI's legitimate potential and the marketing hype that dominates much of the conversation.

Most importantly, she'd develop intuition about the technology's actual capabilities and limitations. That intuition is hard to build from briefings alone.

The Broader Pattern

This disconnect between AI policy and AI practice reflects a broader challenge in technology governance. The officials making decisions about artificial intelligence often come from traditional policy backgrounds, not technical ones. They're briefed by experts with vested interests — academics seeking grants, companies seeking favorable regulations, advocacy groups pushing specific agendas.

Direct experience with the technology won't solve that problem entirely. But it helps. When you've personally wrestled with a tool's quirks and limitations, you're less susceptible to overheated claims about its capabilities.

The irony is sharp: Britain is betting hundreds of millions on AI's potential while the person leading that bet hasn't found it useful enough to adopt herself. Maybe that says more about the current state of AI than any policy announcement could.